Rui Gao

Oper. Res., 2025

Reproducing Kernel Hilbert Space Choice Model.

[BibT_eX]

[DOI]

Proceedings of the 26th ACM Conference on Economics and Computation, 2025

2024

Optimal Robust Policy for Feature-Based Newsvendor.

[BibT_eX]

[DOI]

Luhao Zhang

Jincheng Yang

Manag. Sci., 2024

Wasserstein Distributionally Robust Optimization and Variation Regularization.

[BibT_eX]

[DOI]

Xi Chen

Anton J. Kleywegt

Oper. Res., 2024

Reliable Off-Policy Evaluation for Reinforcement Learning.

[BibT_eX]

[DOI]

Hongyuan Zha

Oper. Res., 2024

Data-driven Multistage Distributionally Robust Linear Optimization with Nested Distance.

[BibT_eX]

[DOI]

Rohit Arora

Yizhe Huang

CoRR, 2024

Non-Convex Robust Hypothesis Testing Using Sinkhorn Uncertainty Sets.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2024

2023

Distributionally Robust Stochastic Optimization with Wasserstein Distance.

[BibT_eX]

[DOI]

Anton J. Kleywegt

Math. Oper. Res., May, 2023

Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels.

[BibT_eX]

[DOI]

Hao Wang

Flávio P. Calmon

J. Mach. Learn. Res., 2023

Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality.

[BibT_eX]

[DOI]

Oper. Res., 2023

Aleatoric and Epistemic Discrimination in Classification.

[BibT_eX]

[DOI]

CoRR, 2023

Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

A Simple Duality Proof for Wasserstein Distributionally Robust Optimization.

[BibT_eX]

[DOI]

Luhao Zhang

Jincheng Yang

CoRR, 2022

Distributionally robust weighted k-nearest neighbors.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Two-Sample Test with Kernel Projected Wasserstein Distance.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Sinkhorn Distributionally Robust Optimization.

[BibT_eX]

[DOI]

CoRR, 2021

Learning While Dissipating Information: Understanding the Generalization Capability of SGLD.

[BibT_eX]

[DOI]

CoRR, 2021

Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators.

[BibT_eX]

[DOI]

Qitian Wu

Hongyuan Zha

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Analyzing the Generalization Capability of SGLD Using Properties of Gaussian Channels.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Generalization Bounds for (Wasserstein) Robust Optimization.

[BibT_eX]

[DOI]

Yang An

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Two-sample Test using Projected Wasserstein Distance.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2021

2020

Two-sample Test using Projected Wasserstein Distance: Breaking the Curse of Dimensionality.

[BibT_eX]

[DOI]

CoRR, 2020

Distributionally Robust $k$-Nearest Neighbors for Few-Shot Learning.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Stein Bridging: Enabling Mutual Reinforcement between Explicit and Implicit Generative Models.

[BibT_eX]

[DOI]

Qitian Wu

Hongyuan Zha

CoRR, 2019

2018

Robust Hypothesis Testing Using Wasserstein Uncertainty Sets.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Wasserstein Distributional Robustness and Regularization in Statistical Learning.

[BibT_eX]

[DOI]